Peripheral venous access is pivotal to a wide range of clinical interventions and is consequently the leading cause of medical injury in the U.S. Complications associated with the procedure are exacerbated in difficult settings, where the rate of success depends heavily on the patient's physiology and the practitioner's experience. My dissertation thesis pertains to the development of imaging and robotic technologies to improve the accuracy and speed of blood draws and IV's. The core technology is an image-guided robotic device that accurately and autonomously introduces a cannula for venous access. The device operates by mapping in real-time the 3D structure of peripheral veins in order to robotically direct a needle into a selected vein. A working prototype has been developed and validated in several studies, the results of which are described in two journal publications. The device combines a 3D near-infrared vein imager, a robot, and computer vision software; these three components form the basis of the three Specific Aims described in this proposal. The Aims fit into the overall dissertation by 1) incorporating the current imaging hardware into a standalone, handheld imaging device; 2) introducing software for the imaging device that assists in selecting suitable cannulation sites; and 3) integrating the imaging device and software with a miniaturized version of the current robot. The outcome of this work will be a compact and low-cost system that is suited for beta-stage development.